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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying machine learning and deep learning algorithms, with a strong focus on portfolio optimization and data-driven insights. Proficient in Python and Spark for building scalable data processing workflows and capable of translating complex technical concepts for diverse stakeholders.
Highest-signal resume keywords
Machine Learning ApplicationStatistical Modeling TechniquesPython ProficiencyData Pipeline DesignAzure and Databricks Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical ModelingData AnalysisPythonPySparkDeep LearningModel ValidationData ProcessingAutomationExperimentation Frameworks
Soft Skills
Excellent CommunicationCreative ThinkingCuriosityIndependent Problem-Solving
Tools & Technologies
AzureDatabricksSparkAI Coding AgentsCI/CD Tools
Industry Keywords
Portfolio OptimizationInsights DiscoverySegmentationForecastingBusiness Objectives
Tech Stack
Tools & technologiesAzurePySparkPythonSpark
About the role
Key responsibilities & impact- Develop solutions for business problems involving portfolio optimization, recommendations, personalization, forecasting, segmentation, and insights discovery.
- Collaborate on complex dataset analysis and develop and deploy advanced machine learning and deep learning algorithms.
- Ensure solutions are robust, scalable, and aligned with business objectives while mentoring junior and mid-level data scientists.
- Stimulate adoption of machine learning and deep learning advancements and frontier algorithms.
- Architect and optimize large-scale data processing workflows on Azure, Databricks, and Spark.
- Design and implement reliable data pipelines and modeling workflows using Python and PySpark.
- Introduce automation and reusable components to improve team productivity and reduce operational overhead.
- Engage with data engineering, product management, and business stakeholders to translate business needs into technical requirements.
- Deliver impactful, end-to-end solutions and drive rapid iteration and continuous improvement.
Requirements
What you’ll need- Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s preferred; PhD a plus.
- Demonstrated success applying machine learning and statistical modeling techniques in production environments to drive measurable business impact.
- Ability to translate complex technical concepts into clear, actionable insights for technical and non-technical stakeholders.
- Experience or strong familiarity with experimentation frameworks, model validation, and rigorous evaluation, ideally in high-stakes decision systems.
- Proven ability to apply machine learning and statistical models in production, balancing accuracy, stability, explainability, and real-world constraints.
- Proficiency in Python for analysis, modeling, and production workflows; experience with distributed data processing such as Spark/PySpark is a plus.
- Experience with modern ML development practices, including version control, CI/CD, and reproducible research and modeling workflows.
- Strong proficiency using AI coding agents and developer tools in a controlled, thoughtful, and production-oriented way.
- Creative, curious, and independent thinker who challenges assumptions and proposes novel approaches.
- Excellent communication skills for explaining complex models and results to technical and non-technical audiences.
Benefits
Comp & perks- Performance based bonus*
- Attendance Bonus*
- Private pension plan
- Meal Allowance
- Casual office and dress code
- Days off*
- Health, dental, and life insurance
- Medicines discounts
- WellHub partnership
- Childcare subsidies
- Discounts on Ambev products*
- Clube Ben partnership
- Scholarship*
- School materials assurance
- Language and training platforms
- Transport allowance